Where MSK AI translation stalls: radiography tasks dominate, OA MRI lags, and a framework for clinical value

AI translation in MSK imaging is selective: narrow, verifiable radiographic tasks (fracture, morphometry) dominate commercial products; OA MRI lags. Clinical value depends on relevant endpoints, workflow fit, and human-AI interaction—not just benchmark performance, authors argue.

• Commercially available MSK AI tools focus on narrow, standardized tasks like radiographic morphometry and fracture detection, which have transparent outputs and clear clinical need.
• Osteoarthritis (OA) assessment via MRI remains a bottleneck due to its multi-tissue, whole-joint, longitudinal nature, poorly suited to binary, single-task AI outputs.
• The authors propose a framework: useful AI = model performance × relevant endpoints × workflow fit × human-AI interaction; translation failures typically reflect deficits in the latter three, not model performance.

Automated summary

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